Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	135,044
2	South Dakota	132,813
3	Rhode Island	129,101
4	Utah	120,146
5	Tennessee	116,613
6	Arizona	115,553
7	Iowa	111,172
8	Oklahoma	110,684
9	Arkansas	109,412
10	Wisconsin	109,150
11	Nebraska	108,288
12	South Carolina	106,952
13	Alabama	105,029
14	Kansas	104,409
15	Mississippi	102,433
16	Indiana	102,305
17	New Jersey	101,905
18	Idaho	100,854
19	Nevada	98,544
20	Illinois	98,292
21	Montana	97,734
22	Georgia	97,328
23	Wyoming	97,166
24	Delaware	97,121
25	Texas	96,218
26	Kentucky	96,135
27	New York	95,813
28	Louisiana	95,597
29	Florida	95,560
30	Missouri	95,237
31	California	92,791
32	Massachusetts	91,850
33	Minnesota	91,842
34	New Mexico	91,269
35	North Carolina	87,506
36	Connecticut	86,965
37	Ohio	86,882
38	Alaska	85,292
39	Colorado	80,398
40	Pennsylvania	80,140
41	West Virginia	78,856
42	Michigan	73,985
43	Virginia	72,396
44	Maryland	67,843
45	District of Columbia	62,930
46	New Hampshire	61,567
47	Washington	48,039
48	Puerto Rico	44,061
49	Oregon	39,021
50	Maine	37,384
51	Vermont	30,623
52	Hawaii	20,968

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Michigan	523
2	New Jersey	487
3	Connecticut	453
4	New York	403
5	Rhode Island	311
6	Pennsylvania	307
7	Delaware	298
8	Alaska	296
9	Massachusetts	267
10	Vermont	259
11	Minnesota	239
12	New Hampshire	237
13	North Carolina	213
14	Florida	207
15	West Virginia	187
16	Maryland	180
17	Tennessee	176
18	Illinois	171
19	District of Columbia	170
20	Colorado	166
21	South Carolina	165
22	South Dakota	155
23	Virginia	154
24	North Dakota	150
25	Maine	148
26	Ohio	141
27	Idaho	134
28	Nebraska	132
29	Iowa	126
30	Puerto Rico	126
31	Texas	125
32	Indiana	117
33	Wyoming	109
34	Georgia	106
35	Kentucky	104
36	Utah	99
37	Washington	97
38	Louisiana	96
39	Wisconsin	96
40	Montana	92
41	Oklahoma	84
42	Arizona	79
43	New Mexico	77
44	Missouri	71
45	Oregon	66
46	California	64
47	Nevada	62
48	Alabama	61
49	Hawaii	61
50	Kansas	53
51	Mississippi	49
52	Arkansas	36

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,756
2	New York	2,554
3	Massachusetts	2,487
4	Rhode Island	2,471
5	Mississippi	2,356
6	Arizona	2,327
7	Connecticut	2,211
8	South Dakota	2,187
9	Louisiana	2,179
10	Alabama	2,146
11	North Dakota	1,965
12	Pennsylvania	1,961
13	Indiana	1,936
14	New Mexico	1,876
15	Arkansas	1,860
16	Illinois	1,857
17	Iowa	1,815
18	South Carolina	1,772
19	Georgia	1,733
20	Tennessee	1,726
21	Michigan	1,712
22	Nevada	1,700
23	Kansas	1,682
24	Texas	1,669
25	Delaware	1,601
26	Ohio	1,591
27	Florida	1,552
28	District of Columbia	1,503
29	California	1,495
30	West Virginia	1,473
31	Missouri	1,461
32	Kentucky	1,371
33	Maryland	1,368
34	Montana	1,344
35	Wisconsin	1,252
36	Minnesota	1,225
37	Oklahoma	1,225
38	Wyoming	1,200
39	Virginia	1,199
40	Nebraska	1,180
41	North Carolina	1,155
42	Idaho	1,096
43	Colorado	1,071
44	New Hampshire	909
45	Washington	696
46	Puerto Rico	661
47	Utah	660
48	Oregon	567
49	Maine	549
50	Alaska	408
51	Vermont	360
52	Hawaii	324

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Delaware	5
2	Kentucky	5
3	New York	4
4	Florida	3
5	Louisiana	3
6	New Jersey	3
7	Rhode Island	3
8	Tennessee	3
9	Arkansas	2
10	California	2
11	District of Columbia	2
12	Massachusetts	2
13	Michigan	2
14	North Carolina	2
15	Ohio	2
16	Texas	2
17	Virginia	2
18	Arizona	1
19	Connecticut	1
20	Georgia	1
21	Illinois	1
22	Indiana	1
23	Iowa	1
24	Kansas	1
25	Maryland	1
26	Mississippi	1
27	Missouri	1
28	New Mexico	1
29	Pennsylvania	1
30	South Carolina	1
31	Utah	1
32	West Virginia	1
33	Wisconsin	1
34	Alabama	0
35	Alaska	0
36	Colorado	0
37	Hawaii	0
38	Idaho	0
39	Maine	0
40	Minnesota	0
41	Montana	0
42	Nebraska	0
43	Nevada	0
44	New Hampshire	0
45	North Dakota	0
46	Oklahoma	0
47	Oregon	0
48	Puerto Rico	0
49	South Dakota	0
50	Vermont	0
51	Washington	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Crowley	Colorado	353,077	1	99
Chattahoochee	Georgia	317,136	2	99
Bent	Colorado	265,914	3	99
Dewey	South Dakota	244,060	4	99
Lincoln	Arkansas	244,011	5	99
Davidson	Tennessee	135,797	204	93
Richland	South Carolina	105,340	1028	67
York	South Carolina	101,609	1198	61
Orange	California	83,779	2030	35
Pierce	Washington	46,754	2903	7

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Foard	Texas	8,658	1	99
Gove	Kansas	8,346	2	99
Jerauld	South Dakota	7,948	3	99
Galax city	Virginia	7,878	4	99
Emporia city	Virginia	7,856	5	99
Orange	California	1,493	1765	43
Davidson	Tennessee	1,291	2013	35
York	South Carolina	1,274	2029	35
Richland	South Carolina	1,268	2038	35
Pierce	Washington	670	2728	13

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.